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Effects of Edge Directions on the Structural Controllability of Complex Networks

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  • Yandong Xiao
  • Songyang Lao
  • Lvlin Hou
  • Michael Small
  • Liang Bai

Abstract

Recent advances indicate that assigning or reversing edge direction can significantly improve the structural controllability of complex networks. For directed networks, approaching the optimal structural controllability can be achieved by detecting and reversing certain “inappropriate” edge directions. However, the existence of multiple sets of “inappropriate” edge directions suggests that different edges have different effects on optimal controllability—that is, different combinations of edges can be reversed to achieve the same structural controllability. Therefore, we classify edges into three categories based on their direction: critical, redundant and intermittent. We then investigate the effects of changing these edge directions on network controllability, and demonstrate that the existence of more critical edge directions implies not only a lower cost of modifying inappropriate edges but also better controllability. Motivated by this finding, we present a simple edge orientation method aimed at producing more critical edge directions—utilizing only local information—which achieves near optimal controllability. Furthermore, we explore the effects of edge direction on the controllability of several real networks.

Suggested Citation

  • Yandong Xiao & Songyang Lao & Lvlin Hou & Michael Small & Liang Bai, 2015. "Effects of Edge Directions on the Structural Controllability of Complex Networks," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-15, August.
  • Handle: RePEc:plo:pone00:0135282
    DOI: 10.1371/journal.pone.0135282
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    Cited by:

    1. Jiang, Lincheng & Zhao, Xiang & Ge, Bin & Xiao, Weidong & Ruan, Yirun, 2019. "An efficient algorithm for mining a set of influential spreaders in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 58-65.
    2. Yin, Yong & Sa, Jiming & Liu, Qiong & Zhang, Chaoyong & Zhou, Jian, 2019. "Robustness analysis of partially interdependent networks with different coupling preferences and multicluster functional nodes in VCMS," Chaos, Solitons & Fractals, Elsevier, vol. 122(C), pages 189-195.
    3. Cui, Pengshuai & Zhu, Peidong & Shao, Chengcheng & Xun, Peng, 2017. "Cascading failures in interdependent networks due to insufficient received support capability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 777-788.

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